Hi @hameerabbasi, This is a small tweak to make sure nonzero returns Tensor's instead of NumPy arrays.
return_offsets_mapping, **kwargs) 1926 stack = tf.stack(stack, axis=0) 1927 elif return_tensors == "pt": -> 1928 stack = torch.stack(stack, dim=0) 1929 elif not return_tensors and len(stack) == 1: 1930 stack = stack[0] TypeError: expected Tensor as element 0 in argument 0...
/home/ljx/.local/lib/python3.6/site-packages/torch/functional.py:445: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /media/nvidia/NVME/p…
_vf很可能是一个特定模块或对象的前缀,而meshgrid是该模块或对象中定义的一个函数。由于这个问题没有提供足够的上下文来确定_vf的确切来源,我无法直接查找_vf.meshgrid的定义或文档。不过,meshgrid函数在NumPy库中非常常见,用于生成网格点坐标。如果_vf与NumPy库有关,那么_vf.meshgrid可能是NumPy中meshgrid函数的一个封...
return x.handle if isinstance(x, np_arrays.ndarray): return x.data return x @@ -1034,7 +1029,6 @@ def gradient(self, " of Tensors or Variables to be differentiated," " but recieved %r" % (target)) num_ndarrays = 0 flat_targets = [] for t in nest.flatten(target): if not ...
tensor. (In theory we could flatten everything to a vector, concat along the single axis and then reshape in rust, but this is a huge hassle and if the return tensors are dynamically sized this becomes even more inconvenient.) Ideally, forward should be able to return a tuple or vector...
I try to use "image.decode_image" to read image file as tensor, but this function returns a tensor without "shape". As said in the doc: Their input and output are all of variable size. If you need fixed size images, pass the output of th...
🐛 Bug I'm not sure if this is expected behaviour or not, but upgrading to the latest version (from 0.8.1) caused my validation_epoch_end to break. It appears that a CUDA tensor is expected for the metric where before the tensor was devic...
Some PyTorch operations, like max and svd, can return a (named)tuple of tensors. There are two issues with their behavior: they do not always return a tuple when they do return a tuple, they can return the extra tensors in strange ways For example: # max over an entire tensor ...
🚀 Feature I am working on medical image analysis, in which for data sample (i.e. medial image) it contains multiple samples (data + label) for training. How can I write my own dataset and dataloader to extract all the tensors from one im...